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Models/SWWAE

SWWAE

Reported on 5 benchmarks across 2 tasks · 2 papers · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision7 results

  • Image ClassificationonSTL-10
    Percentage correct· 2015-06-08
    74.3
    best: 99.64 (µ2Net+ (ViT-L/16))
    SOTA
    Stacked What-Where Auto-encodersarXiv:1506.02351
  • Image ClassificationonSTL-10, 1000 Labels
    Accuracy· 2015-06-08
    74.3
    best: 94.53 (NP-Match)
    SOTA
    Stacked What-Where Auto-encodersarXiv:1506.02351
  • Semi-Supervised Image ClassificationonSTL-10, 1000 Labels
    Accuracy· 2015-06-08
    74.3
    best: 94.53 (NP-Match)
    SOTA
    Stacked What-Where Auto-encodersarXiv:1506.02351
  • Image ClassificationonSTL-10
    Percentage correct· 2018-07-30
    74.33
    best: 99.64 (µ2Net+ (ViT-L/16))
    HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised LearningarXiv:1807.11407
  • Image ClassificationonCIFAR-10
    Percentage correct· 2015-06-08
    92.2
    best: 99.5 (ViT-H/14)
    Stacked What-Where Auto-encodersarXiv:1506.02351
  • Image ClassificationonCIFAR-100
    Percentage correct· uses extra data· 2015-06-08
    69.1
    best: 96.08 (EffNet-L2 (SAM))
    Stacked What-Where Auto-encodersarXiv:1506.02351
  • Image ClassificationonSTL-10
    Percentage correct· 2015-06-08
    74.3
    best: 99.64 (µ2Net+ (ViT-L/16))
    Stacked What-Where Auto-encodersarXiv:1506.02351